Microscopy of live animals had led to many discoveries in neurobiology, immunology, and tumor biology. However, the imaging quality is limited by photobleaching and phototoxicity, which decrease the intensity and disrupt the biosystem over time. To mitigate this effect, I will develop automated event detection that would activate the high-detailed and more disruptive imaging channels only when events of interest are detected in a less disruptive channel. If successful, this would improve measurement duration in real-time tumor imaging and reduce the reoperation rate after tumor surgeries.

I am participating in the SuperUROP to gain valuable knowledge and experience of cutting-edge research. I am excited about the project because it has clear applications in tumor biology and seems to be a great way to combine my skills from both computer science and physics. I hope that this project also helps me decide which field I want to pursue in the future.